Processing data access requests in accordance with a storage unit memory pressure level

ABSTRACT

A method includes determining, by a storage unit of a dispersed storage network (DSN), a storage unit memory pressure level. When the storage unit memory pressure level compares unfavorably to a threshold, the method further includes, in response to a data access request regarding an encoded data slice from a computing device, determining whether the data access request includes an override message or a non-override message. When the data access request includes the non-override message, the method includes generating a storage unit memory pressure level message in accordance with the storage unit memory pressure level and the type of data access request, sending the storage unit memory pressure level message to the computing device, and processing the data access request in accordance with the storage unit memory pressure level message. When the data access request includes the override message, the method further includes processing the data access request.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

Distributed storage systems are known to utilize a three-phase processfor writing consistently in a dispersed storage network (DSN) memory,where the three phases include: (1) A write phase; (2) A commit phase;and (3) A finalize phase. The three phases address consistency issuesthat may arise from different storage units of the DSN holding differentrevisions of encoded data slices, where data is dispersed storage errorencoded to produce the encoded data slices. The three phases are knownto utilize a threshold approach to advance the writing process to thenext phase or to reverse the process when conflicts and errors arise tomaintain consistency of revision storage. Losing contests or unresolvedcontests as a result of overlapping write requests can remain in storageunit memory for a long time and cause storage unit memory pressure.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an embodiment of the dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 10 is a schematic block diagram of an example of a write request inaccordance with the present invention;

FIG. 11 is a schematic block diagram of another example of overlappingwrite requests in accordance with the present invention;

FIGS. 12A-12D are schematic block diagrams of an example of proposalrecords for a set of encoded data slices stored by storage units of theDSN in accordance with the present invention;

FIG. 13 is a schematic block diagram of another embodiment of thedispersed or distributed storage network (DSN) in accordance with thepresent invention;

FIG. 14 is a schematic block diagram of a set of storage units inaccordance with the present invention;

FIG. 15 is a schematic block diagram of another embodiment of thedispersed or distributed storage network (DSN) in accordance with thepresent invention;

FIG. 16 is an example of storage unit memory pressure level messages inaccordance with the present invention;

FIG. 17 is a schematic block diagram of an example of processing dataaccess requests in accordance with a storage unit pressure level inaccordance with the present invention;

FIG. 18 is a schematic block diagram of another example of processingdata access requests in accordance with a storage unit pressure level inaccordance with the present invention; and

FIG. 19 is a logic diagram of an example of a method of processing dataaccess requests in accordance with a storage unit memory pressure levelin accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-8. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN memory 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 60 is shown inFIG. 6. As shown, the slice name (SN) 60 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5 Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of an embodiment of the dispersed ordistributed storage network (DSN) that includes computing devices A-C(e.g., computing devices 12 or 16 of FIG. 1), network 24, and a set ofstorage units (SUs) 36 #1-#5. SUs #1-#5 include proposal records 90-1through 90-5 for an encoded data slice and repair agents 88-1 through88-5. Although shown as a part of each storage unit, repair agents 88-1through 88-5 may be separate devices or part of another device of theDSN. Repair agents 88-1 through 88-5 remove erroneous or unnecessarydata from SUs #1-#5 and facilitate closing out and/or processing dataaccess requests for SUs #1-#5. A data access request includes one ormore of a write request, a write commit, a write finalize, a readrequest, a cleanup request, a delete request, a list request, and anedit request.

FIG. 9 depicts an example of overlapping write requests for a set ofencoded data slices having the same set of slice names. Overlappingwrite requests occur when one set of write requests is pending (e.g.,write finalize requests have not yet been issued) and another set ofwrite requests for a set of encoded data slices having the same set ofslice names is received by the storage units. Sets of encoded dataslices have the same set of slice names when they are regarding the samedata source. In this example, computing devices A, B, and C sendoverlapping write requests 96, 100, and 102 regarding a set of encodeddata slices 98 with the same set of slices names.

To process overlapping write requests (and other overlapping data accessrequests), each storage unit 36 (SU#1-SU#5) stores its own proposalrecord 90-1 through 90-5 for a slice name or for a group of slice names(e.g., an encoded data slice of a data source has its own proposalrecords). A proposal record 90 includes an order listed of pendingtransactions 92 and an ordered list of visible and different versions ofan encoded data slice (EDS) 94 having the same slice name. The proposalrecord 90 may further include an indication of the current revisionlevel of the encoded data slice.

The ordered list of pending transactions 92 include a time ordered listof transaction numbers, or other indication, associated with data accessrequests regarding the slice name that were received while the proposalrecord is open (e.g., write finalize commands have not yet been issuedfor one of the pending write requests). For example, the proposal record90-1 of storage unit #1 includes an ordered list of transaction numbersfor data access requests regarding a first slice name of a set of slicenames.

As a specific example, a first write request from computing device Aregarding a version of an encoded data slice having the first slice namehas a first transaction number (e.g., 0413), a second write request fromcomputing device B regarding another version of the encoded data slicehaving the first slice name has a second transaction number (e.g.,0279), and a third write request from computing device C regardinganother version of the encoded data slice having the first slice namehas a third transaction number (e.g., 0500). Storage unit #1 receivedthe first write request before receiving the second write request andreceived the second write request before receiving the third writerequest. As such the proposal record 90-1 has the first write request(e.g., the first transaction number) in a first priority position, thesecond write request in a second priority position, and the third writerequest in a third priority position.

As another specific example, a write request from computing device Aregarding a version of an encoded data slice having a second slice namehas the first transaction number (e.g., 0413), a write request fromcomputing device B regarding another version of the encoded data slicehaving the second slice name has the second transaction number (e.g.,0279), and a write request from computing device C regarding anotherversion of the encoded data slice having the second slice name has thethird transaction number (e.g., 0500). Storage unit #2 received thewrite request from computing device B before receiving the write requestfrom computing device A and received the write request from computingdevice A before receiving the write request from computing device C. Assuch, the proposal record 90-2 has the write request of computing deviceB (e.g., the second transaction number) in the first priority position,the write request from computing device A in a second priority position,and the write request from computing device C in a third priorityposition.

As another specific example, a write request from computing device Aregarding a version of an encoded data slice having a third slice namehas the first transaction number (e.g., 0413), a write request fromcomputing device B regarding another version of the encoded data slicehaving the third slice name has the second transaction number (e.g.,0279), and a write request from computing device C regarding anotherversion of the encoded data slice having the third slice name has thethird transaction number (e.g., 0500). Storage unit #3 received thewrite request from computing device C before receiving the write requestfrom computing device A and received the write request from computingdevice A before receiving the write request from computing device B. Assuch, the proposal record 90-3 has the write request of computing deviceC (e.g., the third transaction number) in the first priority position,the write request from computing device A in a second priority position,and the write request from computing device B in a third priorityposition. The remaining storage units generate their respective proposalrecords in a similar manner.

In general, a storage unit “opens” a proposal record when it receives anew write request for a version of an encoded data slice having a slicename (i.e., no other write requests are pending). The storage unit sendsthe proposal record to the computing device sending the write request.If there are no overlapping write requests for a set of encoded dataslices having a set of slice names, then the other storage units (SU#2-SU#5) open up proposal records and send them to the computing device.

The computing device interprets the proposal records to determinewhether a threshold number, or more, (e.g., decode threshold number,write threshold number, etc.) of its write requests is in the firstpriority position. When there is not an overlapping write request, thewrite requests will be in the first priority position. As such, thecomputing device sends finalize requests to the storage units. Thestorage units process the finalize request to make the new version ofthe encoded data slices as the most recent set of encoded data slicesand close their respective proposal records.

When there is an overlapping write request (e.g., a storage unit has anopen proposal record for the slice name), the storage unit updates theproposal record with the new write request by placing the new writerequest is a lower priority position than previously received andpending write requests. After updating the proposal record, the storageunit sends the proposal record to the computing device that sent the newwrite request.

As the computing devices receive the proposal records, it determineswhether at least the threshold number of their respective write requestsare in first priority position. If yes, the computing device issues thefinalize commands. If not, the computing device withdraws its writerequests or executes some other fallback position. In addition towithdrawing its write request, the computing device sends cleanuprequests to remove the contest information from the storage units. Ifthe computing device does not send a cleanup request (e.g., thecomputing device crashes, etc.) or the storage unit does not receive acleanup request (e.g., the storage unit crashes, the cleanup request isdropped because of network contention, etc.) the contest may be leftopen indefinitely (i.e., become abandoned).

To remove abandoned contests from memory, when a computing device sendsa write finalize request, the storage unit removes other losing contestsfrom memory. Alternatively, a storage unit may use repair agent 88 tolocate and remove abandoned contests. Abandoned contests are held in thememory of the storage unit and, if active for a long time, may causememory pressure. Memory pressure could lead to degraded performance or aprocess crash. Therefore, to prevent memory pressure, the storage unitskeep track of how many active contests are stored in memory and, ifexperiencing memory pressure, may reject new active contests untilstorage unit memory pressure is reduced (i.e., abandoned contests areremoved).

FIG. 10 is a schematic block diagram of an example of a write request96, 100, and 102 of FIG. 9. The write request includes a transactionnumber field, a slice name (SN) field, an encoded data slice (EDS)field, a current revision level field, and a new revision level field.Each write request in the set of write requests includes the sametransaction number, a different slice name, a different EDS, the samecurrent revision level, and the same new revision level.

FIG. 11 is a schematic block diagram of another example of overlappingwrite requests 96, 100, and 102 for a set of encoded data slices 98. Inthis example, each of computing device A, B, and C encoded the same datasegment into a different set of five encoded data slices. Accordingly,each of computing devices A, B, and C generates five write requests 96-1through 96-5, 100-1 through 100-5, and 102-1 through 102-5. The writerequests from computing device A include the same transaction number of0413 (which may be randomly generated, may be a time stamp, etc.),differing slice names (SN 1_1 through SN 5_1), differing encoded dataslices (EDS A_1_1 through EDS A_5_1), the same current revision level of003, and the next revision level of 004.

The write requests from computing device B include the same transactionnumber of 0279, differing slice names (SN 1_1 through SN 5_1), differingencoded data slices (EDS B_1_1 through EDS B_5_1), the same currentrevision level of 003, and the next revision level of 004.

The write requests from computing device C include the same transactionnumber of 0500, differing slice names (SN 1_1 through SN 5_1), differingencoded data slices (EDS C_1_1 through EDS C_5_1), the same currentrevision level of 003, and the next revision level of 004. A comparisonof the write requests from computing device A with the write requestsfrom computing device B and computing device C yields that the writerequests have the same slice names, the same current revision levels,and the same next revision levels. The write requests differ in thetransaction numbers and in the encoded data slices.

FIGS. 12A-12D are schematic block diagrams of an example of proposalrecords for a set of encoded data slices stored by storage units of theDSN. As shown in FIG. 12A, while the write requests 96, 100, and 102 aresent out at similar times, due to differing latencies and/or processingcapabilities between the computing devices and storage units, therequests are received at different times and, potentially in a differentorder, by the storage units than the order in which they weretransmitted.

Prior to the reception of the write requests, the storage units store acurrent revision level of the set of encoded data slices. As shown inFIG. 12A, storage unit SU#1 stores EDS 1_1, storage unit SU#2 stores EDS2_1, and so on. In this example, the current revision level of theencoded data slices is 003.

In this example, when a storage unit receives a data access request, itopens a proposal record that identifies the data access it justreceived, the current revision level, and an indication that the currentrevision level of the encoded data slice is visible (e.g., can beaccessed by a computing device of the DSN). Upon opening a proposalrecord, the storage unit sends it to the computing device from which itreceived the request. For example, FIG. 12B shows the first proposalrecords sent to computing device A, computing device B, and computingdevice C. FIG. 12C shows updated proposal records sent to computingdevices A and B. FIG. 12D shows updated proposal records sent tocomputing device C.

For example, each of storage units 1, 4, and 5 received the writerequest from computing device A first. Accordingly, each storage unitcreates a proposal record that includes the ordered list of pendingtransactions 92 and the order list of visible different versions of EDS94, which is sent to computing device A. As shown in FIG. 12B, each ofthe ordered list of pending transactions 92-1, 92-4, and 92-5 includethe transaction number of 0413 (the transaction number for the writerequests of computing device A) in the first priority position. Further,each of the order list of visible different versions of EDS 94-1, 94-4,and 94-5 includes an indication that the current revision level of theencoded data slice and the encoded data slice from computing device Aare visible (e.g., for SU #1, EDS 1_1 and EDS A_1_1 are visible).

Continuing with the example, storage unit #2 receives the write requestfrom computing device B first. Accordingly, storage unit #2 creates aproposal record that includes the ordered list of pending transactions92-2 and the order list of visible different versions of EDS 94-2, whichis sent to computing device B. As shown in FIG. 12B, the ordered list ofpending transactions 92-2 includes the transaction number of 0279 (thetransaction number for the write requests of computing device B) in thefirst priority position. Further, the ordered list of visible differentversions of EDS 94-2 includes an indication that the current revisionlevel of the encoded data slice and the encoded data slice fromcomputing device B are visible (e.g., EDS 2_1 and EDS B_2_1 arevisible).

Continuing with the example, storage unit #3 receives the write requestfrom computing device C first. Accordingly, storage unit #3 creates aproposal record that includes the ordered list of pending transactions92-3 and the order list of visible different versions of EDS 94-3, whichis sent to computing device C. As shown in FIG. 12B, the ordered list ofpending transactions 92-3 includes the transaction number of 0500 (thetransaction number for the write requests of computing device C) in thefirst priority position. Further, the ordered list of visible differentversions of EDS 94-3 includes an indication that the current revisionlevel of the encoded data slice and the encoded data slice fromcomputing device C are visible (e.g., EDS 3_1 and EDS C_3_1 arevisible).

As shown in FIG. 12A, after receiving the write requests from computingdevice A, storage units 1, 4, and 5 receive the write request fromcomputing device B, and then receive the write request from computingdevice C. Accordingly, each storage unit updates its proposal record,which are sent to computing devices A, B, and C. As shown in FIGS. 12Cand 12D, each of the ordered list of pending transactions 92-1, 92-4,and 92-5 are updated to include the transaction number of 0279 (thetransaction number for the write requests of computing device B) in thesecond priority position, and the transaction number of 0500 (thetransaction number for the write requests of computing device C) in thethird priority position. Further, each of the order list of visibledifferent versions of EDS 94-1, 94-4, and 94-5 are updated to include anindication that the current revision level of the encoded data slice andthe encoded data slices from computing devices A, B, and C are visible(e.g., for SU #1, EDS 1_1 EDS A_1_1, EDS B_1_1, and C_1_1 are visible).

After receiving the write requests from computing device B, storage unit2 receives the write request from computing device A, and then receivesthe write request from computing device C. Accordingly, storage unit #2updates its proposal record, which is sent to computing devices A, B,and C. For example, as shown in FIGS. 12C and 12D, the ordered list ofpending transactions 92-2 from SU#2 now includes the transaction numberof 0413 (the transaction number for the write requests of computingdevice A) in the second priority position, and the transaction number of0500 (the transaction number for the write requests of computing deviceC) in the third priority position. Further, the ordered list of visibledifferent versions of EDS 94-2 includes an indication that the currentrevision level of the encoded data slice and the encoded data slicesfrom computing devices A, B, and C are visible (e.g., EDS 2_1, EDSB_2_1, EDS A_2_1, and EDS C_2_1 are visible).

After receiving the write requests from computing device C, storage unit3 receives the write request from computing device A, and then receivesthe write request from computing device B. Accordingly, storage unit #3updates its proposal record, which is sent to computing devices A, B,and C. For example, as shown in FIG. 12D, the ordered list of pendingtransactions 92-3 from SU#3 now includes the transaction number of 0413(the transaction number for the write requests of computing device A) inthe second priority position, and the transaction number of 0279 (thetransaction number for the write requests of computing device B) in thethird priority position. Further, the order list of visible differentversions of EDS 94-3 includes an indication that the current revisionlevel of the encoded data slice and the encoded data slices fromcomputing devices A, B, and C are visible (e.g., EDS 3_1, EDS C_3_1, EDSA_3_1, and EDS B_3_1 are visible).

Based on the updated proposal records received by computing devices A,B, and C, each computing device analyzes the proposal records todetermine whether a threshold number of encoded data slices of a desiredversion of the set of encoded data slices are visible and of priority.If so, the computing device completes the write function (e.g., sends awrite finalize request to the storage units). If not, the computingdevice issues a cleanup request to remove the contest information fromthe storage units' memory. In this example, computing device A hasreceived three proposal records indicating its desired version of theset of encoded data slices are visible (e.g., A_1_1, A_4_1, and A_5_1)and of priority (e.g., 0413 is listed first in the transaction section).In this example, three is the threshold number required to perform awrite. Therefore, computing device A can complete the write function.Computing device B and C do not have a threshold number and lose thecontest.

FIG. 13 is a schematic block diagram of another embodiment of thedispersed or distributed storage network (DSN) that includes computingdevices A-C (e.g., computing devices 12 or 16 of FIG. 1), network 24,and a set of storage units (SUs) 36 #1-#5. SUs #1-#5 include proposalrecords 90-1 through 90-5 for an encoded data slice and repair agents88-1 through 88-5. FIG. 13 depicts an example of data access requesterrors resulting in abandoned contests. As discussed above, computingdevice A received proposal records indicating a threshold number of itsdesired version of the set of encoded data slices are visible and ofpriority. Therefore, computing device A sends a set of write finalizerequests 104 to storage units (SUs) #1-#5. Because computing devices Band C did not receive proposal records indicating a threshold number ofits desired version of the set of encoded data slices are visible and ofpriority, computing device B and C send cleanup requests 106 to thestorage units to remove contest information from memory.

However, in the example shown, computing device B is temporarily offline(e.g., computing device B crashed, is not connected to the network,etc.) and was not able to send cleanup requests to the storage units.Also, in this example, SU #1 is offline for a period of time and did notreceive a write finalize request 104 from computing device A or acleanup request from computing device C. Additionally, computing deviceC sent cleanup requests 106, however due to a network error, the cleanuprequest to SU #2 is dropped. When such data access request errors occur,contest information in a proposal record can become abandoned and causestorage unit memory pressure. Memory pressure can lead to degradedperformance or a process crash. To prevent this, storage units keeptrack of how many active contests it can have in memory to functionproperly and implement procedures to remove abandoned contests.

FIG. 14 is a schematic block diagram of a set of storage units 36(SU#1-SU#5) of the DSN. As discussed with reference to FIG. 13, SU #1was offline for a period of time and did not receive a write finalizerequest from computing device A or a cleanup request from computingdevice C and computing device B. Therefore, SU#1 stores a currentrevision level EDS 1_1 (i.e., SU #1 never received a write finalizerequest from computing device A) and also stores abandoned contestinformation from the write requests from computing devices A, B, and C(e.g., slice versions EDS A_1_1, EDS B_1_1, and EDS C_1_1 andtransaction numbers 0413, 0279, and 0500).

Also, as discussed with reference to FIG. 13, computing device B wasoffline for a period of time and never sent cleanup requests to thestorage units. Therefore, SUs #1-#5 store abandoned contest informationfrom computing device B's losing write request (e.g., slice versions EDSB_1_1-B_5_1 and transaction number 0279). While computing device C sentcleanup requests to the storage units, the cleanup request sent to SU #2was dropped due to a network error. Therefore, SU#2 also storesabandoned contest information from computing device C's losing writerequest (e.g., slice version EDS C_2_1 and transaction number 0500).

Each storage unit 36 (SU #1-SU #5) determines a storage unit memorypressure level based on the number of different versions of an encodeddata slice of a set of encoded data slices currently stored in theproposal record of the encoded data slice and memory capacity of thestorage unit. In this example, SU #1 and SU #2 determined a storage unitmemory pressure level that compares unfavorably to a threshold (e.g.,the storage units are storing too many active contests and are underpressure).

FIG. 15 is a schematic block diagram of another embodiment of thedispersed or distributed storage network (DSN) that includes computingdevices A-C (e.g., computing devices 12 or 16 of FIG. 1), network 24,and a set of storage units (SUs) 36 #1-#5. SUs #1-#5 include proposalrecords 90-1 through 90-5 for an encoded data slice and repair agents88-1 through 88-5. FIG. 15 depicts an example of requests regarding aset of encoded data slices 98. As discussed in FIGS. 13-14, computingdevice B was offline temporarily, storage unit (SU) #1 was offlinetemporarily, and a cleanup message from computing device C to SU #2 wasdropped. Because SU #1 was offline, SU #1 did not receive a writefinalize request from computing device A. Here, computing device Aresends a write finalize request 104-1 to SU #1 (e.g., when computingdevice A does not receive confirmation from SU #1). Computing device Cresends cleanup requests 106-1 and 106-2 to SUs #1-2.

Computing device D is sending read requests 108 to the storage units 36(SU#1-SU#5) for the set of encoded data slices 98 and computing device Eis sending write requests 110 to the storage units 36 (SU#1-SU#5) forthe set of encoded data slices 98. The read request 108 includes atransaction number field, a slice name (SN) field, and a currentrevision level field. Each read request in the set of read requests 108includes the same transaction number, a different slice name, and thesame current revision level.

SU #1 is receiving an override message 124-1 from repair agent 88-1 andSU #2 is receiving an override message 124-2 from repair agent 88-2.Because SUs #3-#5 are not under pressure (e.g., the memory pressurelevel discussed in FIG. 14 compares favorably to a threshold), SUs #3-#5will continue to process these data access requests normally. However,because SUs #1-#2 are under pressure (e.g., the memory pressure leveldiscussed in FIG. 14 compares unfavorably to a threshold), SUs #1-#2determine whether the data access request is an override message 124. Ifso, the storage unit will process the override message 124. As anexample, an override message is a cleanup message from the repair agentthat includes an override forcing the storage unit to accept themessage. When the storage unit is under pressure, the repair agent 88adds an override to its messages so that the storage unit does notreject them or take time analyzing whether to accept them.

If the data access request does not include an override message 124, thestorage unit generates a storage unit memory pressure level message inaccordance with the storage unit memory pressure level and the type ofdata access request. The storage unit memory pressure level message maybe an error code rejecting the data access request. Alternatively, thestorage unit memory pressure level message may include an indication ofhow under pressure the storage unit is, an indication of how long thepressure is estimated, and instructions on how to proceed (e.g., wait atime period before trying again, slow down the rate of sending requests,etc.).

FIG. 16 is an example of storage unit memory pressure level messages. Inthis example, there are two categories of storage unit memory pressurelevel messages: 1) storage unit memory pressure level messages inresponse to write requests or write commit requests, and 2) storage unitmemory pressure level messages in response to close-out messages andno-contest requests. When a storage unit determines that the data accessrequest is not the override message, the storage unit generates astorage unit memory pressure level message in accordance with thestorage unit memory pressure level and the type of data access request.

For example, when the type of data access request is a write request orwrite commit request for an encoded data slice of the set of encodeddata slices 98 (e.g., a new contest), the storage unit determines aseverity level of the storage unit memory pressure level. For example,SU #1 has a high severity level because it has three abandoned contestsstored in memory. SU #2 has a medium severity level because it has twoabandoned contests stored in memory. Based on the severity level, thestorage unit memory pressure level message may include one or more of anerror message, a warning message, a rejection of the data accessrequest, an indication of the storage unit memory pressure level (e.g.,percentage of memory capacity, etc.), a request to adjust data accessrequest sending rate (e.g., a scale indicating to slow down the rate offuture data access requests), a request to resend the data accessrequest after a time period, and an estimated time period for thestorage unit memory pressure level.

As specific examples of storage unit memory pressure level messages inresponse to write requests or write commit requests, storage unit (“SU”)memory pressure level message 112 includes an error message indicatingthat SU #1 is currently under pressure and that the data access requestis rejected. SU memory pressure level message 114 includes a messageindicating that SU #1 is at 80% capacity, the data access request isrejected, and to try again in 30 minutes. SU memory pressure levelmessage 116 includes a message indicating that SU #1 is at 80% capacityand that the data access request is rejected. SU memory pressure levelmessage 118 includes a warning message indicating that SU #2 is underpressure and a request to adjust data access request sending rate (e.g.,slow by 20%).

When the data access request is a close-out request or a no-contestrequest, the storage unit generates a memory pressure level message toindicate that the data access request is allowed and to include one ormore of an indication of the storage unit memory pressure level (e.g.,percentage of memory capacity, etc.) and an estimated time period forthe storage unit memory pressure level. A close-out request includes oneor more of a write finalize message and a cleanup message. A no-contestrequest includes one or more of a read request, a delete request, a listrequest, and an edit request. A no-contest request is a data accessrequest that does not create an active contest and a close-out requestsis a data access request that helps get rid of abandoned contests.Because these requests do not create active contests and can help clearup abandoned contests, a storage unit that is under pressure will allowthem but will also notify the sender of the storage unit's state.

As specific examples of storage unit memory pressure level messages inresponse to close-out requests or a no-contest requests, storage unit(“SU”) memory pressure level message 120 includes a message indicatingthat SU #1 is at 80% capacity and that the data access request isallowed. SU memory pressure level message 122 includes a messageindicating that SU #2 is at 65% capacity, that the data access requestis allowed, and that the estimated time for the pressure level is onehour.

FIG. 17 is a schematic block diagram of an example of processing dataaccess requests in accordance with a storage unit pressure level. Inthis example, storage unit (SU) #1 36 is currently experiencing memorypressure as discussed in previous Figures. SU #1 has received a varietyof data access requests regarding different versions of an encoded dataslice. For example, SU #1 receives a write finalize request 104-1 fromcomputing device A, a cleanup request 106-1 from computing device C, aread request 108-1 from computing device D, a write request fromcomputing device E, and an override message from repair agent 88-1.

In response to the data access requests, SU #1 determines whether anyare override messages 124. Here, SU #1 is receiving override message124. Therefore SU #1 processes that message even though it is underpressure. As an example, the override message 124 may includeinstructions to remove abandoned contest information for EDS 2_1_1. Asanother example, override message may include instructions to finalizeEDS 1_1_1 (e.g., if computing device A never resent the finalizemessage). For the data access requests that are not override messages,SU #1 generates a storage unit memory pressure level message inaccordance with the storage unit memory pressure level and the type ofdata access request.

For example, in response to write request 110-1, SU #1 determines aseverity level of the storage unit memory pressure level. In thisexample, SU #1 determines it has a high severity level because it hasthree abandoned contests stored in memory. SU #1 generates and sends SUmemory pressure level message 114 that includes a message indicatingthat SU #1 is at 80% capacity, the data access request is rejected(e.g., the high severity level likely requires a rejection), and to tryagain in 30 minutes. SU #1 then processes write request 110-1 accordingto SU memory pressure level message 114 by rejecting the request.

In response to write finalize request 104-1, SU #1 generates and sendsSU memory pressure level message 120 which includes a message indicatingthat SU #1 is at 80% capacity and that the data access request isallowed. SU #1 then processes write finalize request 104-1 according toSU memory pressure level message 120 to make EDS 1_1_1 the currentrevision.

In response to cleanup request 106-1, SU #1 also generates and sends SUmemory pressure level message 120 which includes a message indicatingthat SU #1 is at 80% capacity and that the data access request isallowed. SU #1 then processes cleanup request 106-1 according to SUmemory pressure level message 120 to remove EDS 3_1_1 contestinformation from memory.

In response to read request 108-1, SU #1 also generates and sends SUmemory pressure level message 120 which includes a message indicatingthat SU #1 is at 80% capacity and that the data access request isallowed. SU #1 then processes read request 108-1 according to SU memorypressure level message 120 to read EDS 1_1_1.

FIG. 18 is a schematic block diagram of another example of processingdata access requests in accordance with a storage unit pressure level.In this example, storage unit (SU) #2 36 is currently experiencingmemory pressure as discussed in previous Figures. SU #2 has received avariety of data access requests regarding different versions of anencoded data slice. For example, SU #2 receives a cleanup request 106-2from computing device C, a read request 108-2 from computing device D, awrite request from computing device E, and an override message 124-2from repair agent 88-2.

In response to the data access requests, SU #2 determines whether anyare override messages 124. Here, SU #2 is receiving override message124-2. SU #2 processes override message 124-2 normally even though it isunder pressure. As an example, the override message 124-2 may includeinstructions to remove abandoned contest information for EDS 2_2_1. Forthe data access requests that are not override messages, SU #2 generatesa storage unit memory pressure level message in accordance with thestorage unit memory pressure level and the type of data access request.

For example, in response to write request 110-2, SU #2 determines aseverity level of the SU memory pressure level. In this example, SU #2determines that it has a medium severity level because it has twoabandoned contests stored in memory. SU #2 generates and sends SU memorypressure level message 118 to computing device E which includes awarning message indicating that SU #2 is under pressure (e.g., a mediumseverity level does not require a data access request rejection in thisexample) and a request to adjust data access request sending rate (e.g.,slow by 20%). SU #2 then processes write request 110-2 according to SUmemory pressure level message 118 by processing the request.

In response to cleanup request 106-1, SU #2 generates and sends SUmemory pressure level message 122 which includes a message indicatingthat SU #2 is at 65% capacity, that the data access request is allowed,and that the estimated time for the pressure level is one hour. SU #2then processes cleanup request 106-2 according to SU memory pressurelevel message 122 to remove EDS 3_2_1 contest information from memory.

In response to read request 108-2, SU #2 also generates and sends SUmemory pressure level message 122 which includes a message indicatingthat SU #2 is at 65% capacity, that the data access request is allowed,and that the estimated time for the pressure level is one hour. SU #2then processes read request 108-2 according to SU memory pressure levelmessage 120 to read EDS 1_2_1.

FIG. 19 is a logic diagram of an example of a method of processing dataaccess requests in accordance with a storage unit memory pressure level.The method begins at step 126 where a storage unit of a dispersedstorage network (DSN) determines a storage unit memory pressure levelbased on a number of different versions of an encoded data slice of aset of encoded data slices currently stored in a proposal record of theencoded data slice and memory capacity of the storage unit. The proposalrecord includes an ordered list of pending transactions for the encodeddata slice and an ordered list of different versions of the encoded dataslice.

An abandoned contest is a version of an encoded data slice that is leftin memory after the end of the contest (e.g., a losing contest in anoverlapping write request that is not cleaned up, etc.) or at thebeginning of a new contest (e.g., a winning contest in an overlappingwrite request that is not finalized, etc.). There are many ways acontest may become abandoned on a storage unit. For example, a computingdevice that sent the data access request may crash, the storage unit maycrash, a request can be dropped due to network contention, etc.Abandoned contests are held in the memory of the storage unit and, ifactive for a long time, may cause memory pressure. Memory pressure couldlead to degraded performance or a process crash. Therefore, to preventmemory pressure, the storage units keep track of how many activecontests are stored in memory and may reject new active contests untilstorage unit memory pressure is reduced (i.e., abandoned contests areremoved).

The method continues with step 128 where the storage unit determineswhether the storage unit memory pressure level compares unfavorably to athreshold. When the storage unit memory pressure level comparesfavorably to the threshold, the method continues with step 130 where thestorage unit processes data access requests normally.

When the storage unit memory pressure level compares unfavorably to thethreshold at step 128, the method continues with step 132 where inresponse to a data access request regarding the encoded data slice froma computing device (“CD”) of the DSN, the storage unit determineswhether the data access request includes an override message or anon-override message. For example, an override message is sent from arepair agent of the storage unit to cleanup abandoned contests. A repairagent removes erroneous or unnecessary data from a storage unit (e.g.,is part of the storage unit or a separate device) and facilitatesclosing out and/or processing data access requests for the storage unit.The override forces the storage unit to accept messages from the repairagent. As an example, the override message may include instructions tofinalize an abandoned contest involving the “winning” version of anencoded data slice from an overlapping write request. As anotherexample, the override message may include instructions to cleanup anabandoned contest involving the “losing” version of an encoded dataslice from an overlapping write request. When the data access requestincludes the override message, the method continues with step 134 wherethe storage unit processes the data access request.

When the data access request includes a non-override message, the methodcontinues with step 136 where the storage unit generates a storage unitmemory pressure level message in accordance with the storage unit memorypressure level and the type of data access request. When the type ofdata access request is a write request or write commit request for theencoded data slice, the storage unit determines a severity level of thestorage unit memory pressure level. Based on the severity level, thestorage unit memory pressure level message may include one or more of anerror message, a warning message, a rejection of the data accessrequest, an indication of the storage unit memory pressure level (e.g.,percentage of memory capacity, etc.), a request to adjust data accessrequest sending rate (e.g., a scale indicating to slow down the rate offuture data access requests), a request to resend the data accessrequest after a time period, and an estimated time period for thestorage unit memory pressure level. As an example, when the severitylevel is high, the storage unit memory pressure level message may rejectthe data access request. When the severity level is medium, the storageunit memory pressure level message may accept the data access requestbut send a request to adjust data access request sending rate (e.g.,slow down by 20%).

When the data access request is a close-out request or a no-contestrequest, the storage unit generates a memory pressure level message toindicate that the data access request is allowed and to include one ormore of an indication of the storage unit memory pressure level (e.g.,percentage of memory capacity, etc.) and an estimated time period forthe storage unit memory pressure level. A close-out request includes oneor more of a write finalize message and a cleanup message. A no-contestrequest includes one or more of a read request, a delete request, listrequest, and an edit request. A no-contest request is a data accessrequest that does not create an active contest and a close-out requestsis a data access request that helps get rid of abandoned contests.Because these requests do not create active contests and can help clearup abandoned contests, a storage unit that is under pressure will allowthem but will also notify the computing device of the storage unit'sstate.

The storage unit sends the storage unit memory pressure level message tothe computing device. The method continues with step 138 where thestorage unit processes the data access request in accordance withstorage unit memory pressure level message.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, text, graphics, audio, etc. any of which may generally bereferred to as ‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. For some industries, anindustry-accepted tolerance is less than one percent and, for otherindustries, the industry-accepted tolerance is 10 percent or more. Otherexamples of industry-accepted tolerance range from less than one percentto fifty percent. Industry-accepted tolerances correspond to, but arenot limited to, component values, integrated circuit process variations,temperature variations, rise and fall times, thermal noise, dimensions,signaling errors, dropped packets, temperatures, pressures, materialcompositions, and/or performance metrics. Within an industry, tolerancevariances of accepted tolerances may be more or less than a percentagelevel (e.g., dimension tolerance of less than +/−1%). Some relativitybetween items may range from a difference of less than a percentagelevel to a few percent. Other relativity between items may range from adifference of a few percent to magnitude of differences.

As may also be used herein, the term(s) “configured to”, “operablycoupled to”, “coupled to”, and/or “coupling” includes direct couplingbetween items and/or indirect coupling between items via an interveningitem (e.g., an item includes, but is not limited to, a component, anelement, a circuit, and/or a module) where, for an example of indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.

As may even further be used herein, the term “configured to”, “operableto”, “coupled to”, or “operably coupled to” indicates that an itemincludes one or more of power connections, input(s), output(s), etc., toperform, when activated, one or more its corresponding functions and mayfurther include inferred coupling to one or more other items. As maystill further be used herein, the term “associated with”, includesdirect and/or indirect coupling of separate items and/or one item beingembedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may be used herein, one or more claims may include, in a specificform of this generic form, the phrase “at least one of a, b, and c” orof this generic form “at least one of a, b, or c”, with more or lesselements than “a”, “b”, and “c”. In either phrasing, the phrases are tobe interpreted identically. In particular, “at least one of a, b, and c”is equivalent to “at least one of a, b, or c” and shall mean a, b,and/or c. As an example, it means: “a” only, “b” only, “c” only, “a” and“b”, “a” and “c”, “b” and “c”, and/or “a”, “b”, and “c”.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, “processing circuitry”, and/or “processing unit”may be a single processing device or a plurality of processing devices.Such a processing device may be a microprocessor, micro-controller,digital signal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, processing circuitry, and/or processing unitmay be, or further include, memory and/or an integrated memory element,which may be a single memory device, a plurality of memory devices,and/or embedded circuitry of another processing module, module,processing circuit, processing circuitry, and/or processing unit. Such amemory device may be a read-only memory, random access memory, volatilememory, non-volatile memory, static memory, dynamic memory, flashmemory, cache memory, and/or any device that stores digital information.Note that if the processing module, module, processing circuit,processing circuitry, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,processing circuitry and/or processing unit implements one or more ofits functions via a state machine, analog circuitry, digital circuitry,and/or logic circuitry, the memory and/or memory element storing thecorresponding operational instructions may be embedded within, orexternal to, the circuitry comprising the state machine, analogcircuitry, digital circuitry, and/or logic circuitry. Still further notethat, the memory element may store, and the processing module, module,processing circuit, processing circuitry and/or processing unitexecutes, hard coded and/or operational instructions corresponding to atleast some of the steps and/or functions illustrated in one or more ofthe Figures. Such a memory device or memory element can be included inan article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with one or more other routines. In addition, a flow diagrammay include an “end” and/or “continue” indication. The “end” and/or“continue” indications reflect that the steps presented can end asdescribed and shown or optionally be incorporated in or otherwise usedin conjunction with one or more other routines. In this context, “start”indicates the beginning of the first step presented and may be precededby other activities not specifically shown. Further, the “continue”indication reflects that the steps presented may be performed multipletimes and/or may be succeeded by other activities not specificallyshown. Further, while a flow diagram indicates a particular ordering ofsteps, other orderings are likewise possible provided that theprinciples of causality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form asolid-state memory, a hard drive memory, cloud memory, thumb drive,server memory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method comprises: determining, by a storageunit of a dispersed storage network (DSN), a storage unit memorypressure level based on a number of different versions of an encodeddata slice of a set of encoded data slices currently stored in aproposal record of the encoded data slice and memory capacity of thestorage unit, wherein the proposal record includes an ordered list ofpending transactions for the encoded data slice and an ordered list ofdifferent versions of the encoded data slice; and when the storage unitmemory pressure level compares unfavorably to a threshold: in responseto a data access request regarding the encoded data slice from acomputing device of the DSN, determining whether the data access requestincludes an override message or a non-override message; when the dataaccess request includes the non-override message: generating, by thestorage unit, a storage unit memory pressure level message in accordancewith the storage unit memory pressure level and a type of data accessrequest; sending, by the storage unit, the storage unit memory pressurelevel message to the computing device; and processing, by the storageunit, the data access request in accordance with the storage unit memorypressure level message; and when the data access request includes theoverride message: processing, by the storage unit, the data accessrequest.
 2. The method of claim 1, wherein generating the storage unitmemory pressure level message further comprises: when the data accessrequest includes one or more of: one or more write requests and one ormore write commit requests: determining, by the storage unit, a severitylevel of the storage unit memory pressure level; and generating, by thestorage unit, the storage unit memory pressure level message based onthe severity level to include one or more of: an error message; awarning message; a rejection of the data access request an indication ofthe storage unit memory pressure level; a request to adjust data accessrequest sending rate; a request to resend the data access request aftera time period; and an estimated time period for the storage unit memorypressure level.
 3. The method of claim 1, wherein generating the storageunit memory pressure level message further comprises: when the dataaccess request includes one or more of: one or more close-out requestsand one or more no-contest requests; generating, by the storage unit,the storage unit memory pressure level message to indicate that the dataaccess request is allowed and to include one or more of: an indicationof the storage unit memory pressure level; and an estimated time periodfor the storage unit memory pressure level.
 4. The method of claim 3,wherein the one or more close-out requests include: one or more writefinalize requests; and one or more cleanup requests.
 5. The method ofclaim 3, wherein the one or more no-contest requests include: one ormore read requests; one or more delete requests; one or more listrequests; and one or more edit requests.
 6. The method of claim 1,wherein the data access request includes a slice name for the encodeddata slice, a transaction number, a type of request, and a currentrevision level of the encoded data slice.
 7. A storage unit of adispersed storage network (DSN), the storage unit comprises: aninterface; memory; and a processing module operably coupled to thememory and the interface, wherein the processing module is operable to:determine a storage unit memory pressure level based on a number ofdifferent versions of an encoded data slice of a set of encoded dataslices currently stored in a proposal record of the encoded data sliceand memory capacity of the storage unit, wherein the proposal recordincludes an ordered list of pending transactions for the encoded dataslice and an ordered list of different versions of the encoded dataslice; and when the storage unit memory pressure level comparesunfavorably to a threshold: in response to a data access requestregarding the encoded data slice from a computing device of the DSN,determining whether the data access request includes an override messageor a non-override message; when the data access request includes thenon-override message: generating, by the storage unit, a storage unitmemory pressure level message in accordance with the storage unit memorypressure level and a type of data access request; sending, by thestorage unit, the storage unit memory pressure level message to thecomputing device; and processing, by the storage unit, the data accessrequest in accordance with the storage unit memory pressure levelmessage; and when the data access request includes the override message:processing, by the storage unit, the data access request.
 8. The storageunit of claim 7, wherein the processing module is further operable togenerate the storage unit memory pressure level message by: when thedata access request includes one or more of: one or more write requestsand one or more write commit requests: determining a severity level ofthe storage unit memory pressure level; and generating the storage unitmemory pressure level message based on the severity level to include oneor more of: an error message; a warning message; a rejection of the dataaccess request an indication of the storage unit memory pressure level;a request to adjust data access request sending rate; a request toresend the data access request after a time period; and an estimatedtime period for the storage unit memory pressure level.
 9. The storageunit of claim 7, wherein the processing module is further operable togenerate the storage unit memory pressure level message by: when thedata access request includes one or more of: one or more close-outrequests and one or more no-contest requests; generating the storageunit memory pressure level message to indicate that the data accessrequest is allowed and to include one or more of: an indication of thestorage unit memory pressure level; and an estimated time period for thestorage unit memory pressure level.
 10. The storage unit of claim 9,wherein the one or more close-out requests include: one or more writefinalize requests; and one or more cleanup requests.
 11. The storageunit of claim 9, wherein the one or more no-contest requests include:one or more read requests; one or more delete requests; one or more listrequests; and one or more edit requests.
 12. The storage unit of claim7, wherein the data access request includes a slice name for the encodeddata slice, a transaction number, a type of request, and a currentrevision level of the encoded data slice.